import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def 							UpperCamelCase		(			__lowercase		:					int		,__lowercase		:					int      ):
		'''simple docstring'''




		assert isinstance(__lowercase		,__lowercase      )
		assert dataset.num_rows == 4
		assert dataset.num_columns == 1
		assert dataset.column_names == ["text"]
		for feature, expected_dtype in expected_features.items():
				assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('keep_in_memory'		,[False, True]      )
def 							UpperCamelCase		(			__lowercase		:					str		,__lowercase		:					Union[str, Any]		,__lowercase		:					Any      ):
		'''simple docstring'''




		A_						:							List[str]      = tmp_path / 'cache'
		A_						:							Optional[Any]      = {'text': 'string'}
		with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
				A_						:							Optional[int]      = TextDatasetReader(__lowercase		,cache_dir=__lowercase		,keep_in_memory=__lowercase      ).read()
		_check_text_dataset(__lowercase		,__lowercase      )




@pytest.mark.parametrize(
    'features'		,[
        None,
        {'text': 'string'},
        {'text': 'int32'},
        {'text': 'float32'},
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Tuple		,__lowercase		:					Tuple		,__lowercase		:					Optional[Any]      ):
		'''simple docstring'''




		A_						:							Union[str, Any]      = tmp_path / 'cache'
		A_						:							int      = {'text': 'string'}
		A_						:							Dict      = features.copy() if features else default_expected_features
		A_						:							List[str]      = (
		    Features({feature: Value(__lowercase      ) for feature, dtype in features.items()}      ) if features is not None else None
		)
		A_						:							Optional[Any]      = TextDatasetReader(__lowercase		,features=__lowercase		,cache_dir=__lowercase      ).read()
		_check_text_dataset(__lowercase		,__lowercase      )




@pytest.mark.parametrize('split'		,[None, NamedSplit('train'      ), 'train', 'test']      )
def 							UpperCamelCase		(			__lowercase		:					str		,__lowercase		:					List[Any]		,__lowercase		:					Optional[int]      ):
		'''simple docstring'''




		A_						:							Any      = tmp_path / 'cache'
		A_						:							Tuple      = {'text': 'string'}
		A_						:							int      = TextDatasetReader(__lowercase		,cache_dir=__lowercase		,split=__lowercase      ).read()
		_check_text_dataset(__lowercase		,__lowercase      )
		assert dataset.split == split if split else "train"




@pytest.mark.parametrize('path_type'		,[str, list]      )
def 							UpperCamelCase		(			__lowercase		:					int		,__lowercase		:					Optional[int]		,__lowercase		:					int      ):
		'''simple docstring'''




		if issubclass(__lowercase		,__lowercase      ):
				A_						:							List[Any]      = text_path
		elif issubclass(__lowercase		,__lowercase      ):
				A_						:							int      = [text_path]
		A_						:							Any      = tmp_path / 'cache'
		A_						:							int      = {'text': 'string'}
		A_						:							Union[str, Any]      = TextDatasetReader(__lowercase		,cache_dir=__lowercase      ).read()
		_check_text_dataset(__lowercase		,__lowercase      )




def 							UpperCamelCase		(			__lowercase		:					int		,__lowercase		:					Dict		,__lowercase		:					str=("train",)      ):
		'''simple docstring'''




		assert isinstance(__lowercase		,__lowercase      )
		for split in splits:
				A_						:							Dict      = dataset_dict[split]
				assert dataset.num_rows == 4
				assert dataset.num_columns == 1
				assert dataset.column_names == ["text"]
				for feature, expected_dtype in expected_features.items():
						assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('keep_in_memory'		,[False, True]      )
def 							UpperCamelCase		(			__lowercase		:					Optional[Any]		,__lowercase		:					Dict		,__lowercase		:					str      ):
		'''simple docstring'''




		A_						:							List[str]      = tmp_path / 'cache'
		A_						:							Optional[int]      = {'text': 'string'}
		with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
				A_						:							Dict      = TextDatasetReader({'train': text_path}		,cache_dir=__lowercase		,keep_in_memory=__lowercase      ).read()
		_check_text_datasetdict(__lowercase		,__lowercase      )




@pytest.mark.parametrize(
    'features'		,[
        None,
        {'text': 'string'},
        {'text': 'int32'},
        {'text': 'float32'},
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					str		,__lowercase		:					List[str]		,__lowercase		:					Optional[Any]      ):
		'''simple docstring'''




		A_						:							Optional[Any]      = tmp_path / 'cache'
		# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
		A_						:							Optional[Any]      = {'text': 'string'}
		A_						:							Union[str, Any]      = features.copy() if features else default_expected_features
		A_						:							Optional[Any]      = (
		    Features({feature: Value(__lowercase      ) for feature, dtype in features.items()}      ) if features is not None else None
		)
		A_						:							Optional[int]      = TextDatasetReader({'train': text_path}		,features=__lowercase		,cache_dir=__lowercase      ).read()
		_check_text_datasetdict(__lowercase		,__lowercase      )




@pytest.mark.parametrize('split'		,[None, NamedSplit('train'      ), 'train', 'test']      )
def 							UpperCamelCase		(			__lowercase		:					str		,__lowercase		:					Tuple		,__lowercase		:					str      ):
		'''simple docstring'''




		if split:
				A_						:							int      = {split: text_path}
		else:
				A_						:							int      = 'train'
				A_						:							List[Any]      = {'train': text_path, 'test': text_path}
		A_						:							Union[str, Any]      = tmp_path / 'cache'
		A_						:							Union[str, Any]      = {'text': 'string'}
		A_						:							Tuple      = TextDatasetReader(__lowercase		,cache_dir=__lowercase      ).read()
		_check_text_datasetdict(__lowercase		,__lowercase		,splits=list(path.keys()      )      )
		assert all(dataset[split].split == split for split in path.keys()      )







import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


_UpperCAmelCase          =						pytest.mark.integration




@pytest.mark.parametrize('path'		,['paws', 'csv']      )
def 							UpperCamelCase		(			__lowercase		:					Optional[Any]		,__lowercase		:					Tuple      ):
		'''simple docstring'''




		inspect_dataset(__lowercase		,__lowercase      )
		A_						:							Optional[Any]      = path + '.py'
		assert script_name in os.listdir(__lowercase      )
		assert "__pycache__" not in os.listdir(__lowercase      )




@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'      )
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'      )
@pytest.mark.parametrize('path'		,['accuracy']      )
def 							UpperCamelCase		(			__lowercase		:					Any		,__lowercase		:					Union[str, Any]      ):
		'''simple docstring'''




		inspect_metric(__lowercase		,__lowercase      )
		A_						:							Optional[Any]      = path + '.py'
		assert script_name in os.listdir(__lowercase      )
		assert "__pycache__" not in os.listdir(__lowercase      )




@pytest.mark.parametrize(
    'path, config_name, expected_splits'		,[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					List[str]		,__lowercase		:					Dict		,__lowercase		:					Dict      ):
		'''simple docstring'''




		A_						:							List[Any]      = get_dataset_config_info(__lowercase		,config_name=__lowercase      )
		assert info.config_name == config_name
		assert list(info.splits.keys()      ) == expected_splits




@pytest.mark.parametrize(
    'path, config_name, expected_exception'		,[
        ('paws', None, ValueError),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Dict		,__lowercase		:					List[Any]		,__lowercase		:					int      ):
		'''simple docstring'''




		with pytest.raises(__lowercase      ):
				get_dataset_config_info(__lowercase		,config_name=__lowercase      )




@pytest.mark.parametrize(
    'path, expected'		,[
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					str		,__lowercase		:					str      ):
		'''simple docstring'''




		A_						:							Any      = get_dataset_config_names(__lowercase      )
		assert expected in config_names




@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'		,[
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Tuple		,__lowercase		:					str		,__lowercase		:					Optional[Any]      ):
		'''simple docstring'''




		A_						:							Optional[int]      = get_dataset_infos(__lowercase      )
		assert list(infos.keys()      ) == expected_configs
		A_						:							Any      = expected_configs[0]
		assert expected_config in infos
		A_						:							Tuple      = infos[expected_config]
		assert info.config_name == expected_config
		assert list(info.splits.keys()      ) == expected_splits_in_first_config




@pytest.mark.parametrize(
    'path, expected_config, expected_splits'		,[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Any		,__lowercase		:					Optional[Any]		,__lowercase		:					Dict      ):
		'''simple docstring'''




		A_						:							Optional[Any]      = get_dataset_infos(__lowercase      )
		assert expected_config in infos
		A_						:							str      = infos[expected_config]
		assert info.config_name == expected_config
		assert list(info.splits.keys()      ) == expected_splits




@pytest.mark.parametrize(
    'path, config_name, expected_exception'		,[
        ('paws', None, ValueError),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Tuple		,__lowercase		:					Tuple		,__lowercase		:					str      ):
		'''simple docstring'''




		with pytest.raises(__lowercase      ):
				get_dataset_split_names(__lowercase		,config_name=__lowercase      )






